Displaying 4 results from an estimated 4 matches for "fitcontrol".
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biocontrol
2011 Aug 28
1
Trying to extract probabilities in CARET (caret) package with a glmStepAIC model
...erything was working fine I got the results, confussion matrix etc.
BUT for obtaining the AUC and predicted probabilities I had to add " classProbs = TRUE," in the trainControl. Thereafter everytime I run train I get this message:
"undefined columns selected"
I copy the syntax:
fitControl <- trainControl(method = "cv", number = 10, classProbs = TRUE,returnResamp = "all", verboseIter = FALSE)
glmFit <- train(Descr, Categ, method = "glmStepAIC",tuneLength = 4,trControl = fitControl)
Thank you.
Best regards,
Jon Toledo, MD
Postdoctoral fellow
Unive...
2012 May 30
1
caret() train based on cross validation - split dataset to keep sites together?
...??? 14.2??????????26.9
15687??? 1980-06-03????????? 13.8??????????28.9
18994??? 1980-04-05????????? 8.4???????????16.4
18994??? 1980-04-06????????? 8.3???????????12.6
90342??? 1980-07-13????????? 18.9??????????22.3
90342??? 1980-07-14????????? 19.3??????????28.4
EXAMPLE SCRIPT FOR MODEL FITTING
fitControl <- trainControl(method = "repeatedcv", number=10, repeats=3)
tuning <- read.table("temptunegrid.txt",head=T,sep=",")
tuning
# # Model with 100 iterations
registerDoMC(4)
tempmod100its <- train(watmntemp~tempa + tempb + tempc + tempd + tempe +
netarea + net...
2017 Dec 02
0
How can you find the optimal number of values to randomly sample to optimize random forest classification without trial and error?
...enttrainingset)
This is the final data frame being used in the classification algorithm. My
goal of this post is to figure out how to identify the optimal "s" value so
that the highest ROC is achieved. I am using "rf" from the caret package to
do classification.
library(caret)
fitControl <-trainControl(method = "LOOCV", classProbs = T, savePredictions = T)
model <- train(status ~ ., data = dataset, method = "rf", trControl =
fitControl)
How can I automate it to start "s" at 5000, change it to another value, and
based on the change in ROC, keep c...
2011 May 28
0
how to train ksvm with spectral kernel (kernlab) in caret?
...o
train a svm with a spectral kernel from the kernlab package. Sadly
a svm with spectral kernel is not among the many methods in caret...
using caret to train svmRadial:
------------------
library(caret)
library(kernlab)
data(iris)
TrainData<- iris[,1:4]
TrainClasses<- iris[,5]
set.seed(2)
fitControl$summaryFunction<- Rand
svmNew<- train(TrainData, TrainClasses,
method = "svmRadial",
preProcess = c("center", "scale"),
metric = "cRand",
tuneLength = 4)
svmNew
-------------------
here is an example on how to train the
ksvm with spectral ker...